Social botnets have become an important phenomenon on social media. There are
many ways in which social bots can disrupt or influence online discourse, such
as, spam hashtags, scam twitter users, and astroturfing. In this paper we
considered one specific social botnet in Twitter to understand how it grows
over time, how the content of tweets by the social botnet differ from regular
users in the same dataset, and lastly, how the social botnet may have
influenced the relevant discussions. Our analysis is based on a qualitative
coding for approximately 3000 tweets in Arabic and English from the Syrian
social bot that was active for 35 weeks on Twitter before it was shutdown. We
find that the growth, behavior and content of this particular botnet did not
specifically align with common conceptions of botnets. Further we identify
interesting aspects of the botnet that distinguish it from regular users.

本文研究了一种特定的 Twitter 社交机器人网络，分析了其增长、内容和行为，以及该机器人网络对相关讨论的影响。通过对约 3000 条推文进行定性编码分析，发现该机器人网络的增长、行为和内容并不符合通常机器人网络的概念，并识别了与普通用户不同的有趣方面。